A set of entities may include different entities that are each associated with a different level of risk. For example, a first entity may pose a first degree of risk that is substantially higher as compared to a second entity that is associated with a second degree of risk. It may therefore be desirable to determine relative amounts of risk for each entity in a set. For example, determining that a particular entity is associated with an unusually high level of risk may allow remedial actions to be taken with respect to that entity. Determining this information, however, can be a time consuming and error prone task, especially where then are a substantially number of entities and when degrees of risk may depend on data elements from various source inputs of different types (e.g., structured source inputs, unstructured source inputs, third-party source inputs, etc.).
It would be desirable to provide systems and methods to process data elements received via source inputs in a way that provides faster, more accurate results and that allows for flexibility and effectiveness when responding to those results.